• Radiation Oncology Journal
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• v.32 no.1
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• pp.23-30
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• 2014

Purpose: The goal of this study is to determine whether the magnitude of overlap between planning target volume (PTV) and rectum ($Rectum_{overlap}$) or PTV and bladder ($Bladder_{overlap}$) in prostate cancer volumetric-modulated arc therapy (VMAT) is predictive of the dose-volume relationships achieved after optimization, and to identify predictive equations and cutoff values using these overlap volumes beyond which the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) dose-volume constraints are unlikely to be met. Materials and Methods: Fifty-seven patients with prostate cancer underwent VMAT planning using identical optimization conditions and normalization. The PTV (for the 50.4 Gy primary plan and 30.6 Gy boost plan) included 5 to 10 mm margins around the prostate and seminal vesicles. Pearson correlations, linear regression analyses, and receiver operating characteristic (ROC) curves were used to correlate the percentage overlap with dose-volume parameters. Results: The percentage $Rectum_{overlap}$ and $Bladder_{overlap}$ correlated with sparing of that organ but minimally impacted other dose-volume parameters, predicted the primary plan rectum $V_{45}$ and bladder $V_{50}$ with $R^2$ = 0.78 and $R^2$ = 0.83, respectively, and predicted the boost plan rectum $V_{30}$ and bladder $V_{30}$ with $R^2$ = 0.53 and $R^2$ = 0.81, respectively. The optimal cutoff value of boost $Rectum_{overlap}$ to predict rectum $V_{75}$ >15% was 3.5% (sensitivity 100%, specificity 94%, p < 0.01), and the optimal cutoff value of boost $Bladder_{overlap}$ to predict bladder $V_{80}$ >10% was 5.0% (sensitivity 83%, specificity 100%, p < 0.01). Conclusion: The degree of overlap between PTV and bladder or rectum can be used to accurately guide physicians on the use of interventions to limit the extent of the overlap region prior to optimization.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.